Benzene Exposure Assessment at Indoor, Outdoor and Personal Levels. The French Contribution to the Life MACBETH Programme

Many VOC represent hazards to human health through chronic exposure. Recent European and world-wide legislation proposes limit values for ambient concentrations of these compounds. However, very little experimental data exists for true population exposure. In 1996, the European MACBETH initiative set out to measure population exposure to benzene in six European cities. This study details the French contribution to this program. Six campaigns were carried out, each comprising measurements at 100 outdoor sites and the participation of 50 non-smoking volunteers who wore personal samplers and had passive monitors installed in their homes. Iso-concentration maps were drawn for each campaign and the results showed that outdoor concentrations were significantly lower than indoors. Almost 75% of the volunteers were exposed to mean concentrations higher than the limit value of 5µgm³. It is demonstrated that personal exposure levels cannot be deduced simply by combining indoor and outdoor background concentrations. It is also shown that there is need for better knowledge of the contributions to overall exposure of outdoor microenvironments and the authors hope that future European directives will take this into account.     

大气固定污染源低浓度颗粒物采样及分析技术研究进展

简述了我国现阶段大气固定污染源颗粒物监测中遇到的问题及低浓度颗粒物采样与分析技术研究的必要性,归纳了国外低浓度颗粒物采样分析技术要点,包括大体积采样、滤筒上游采样设备堆积颗粒物的回收、有效称重步骤的确立等,并对我国开展低浓度颗粒物采样及分析技术研究提出了相关建议.     

室内空气中的气态多环芳烃的被动采样监测

利用自制被动采样装置,在2011年秋冬季对南京市部分地区室内空气中5种气态多环芳烃(PAHs)(萘、苊烯、苊、芴、菲)进行了为期100d的连续采样检测,被动采样器的采样速率为0.012m3/d,5种PAHs的回收率在63%～105%之间,方法检出限在1.1～2.4ng范围内。结果表明,南京市5处不同室内环境空气中萘的浓度最高,占总量的90%以上。室内环境空气中5种PAHs的总浓度为230～1564ng/m3。住宅内人体对5种PAHs的暴露速率为479～560ng/h。     

Use of Market Data to Assess Bushmeat Hunting Sustainability in Equatorial Guinea

Abstract: Finding an adequate measure of hunting sustainability for tropical forests has proved difficult. Many researchers have used urban bushmeat market surveys as indicators of hunting volumes and composition, but no analysis has been done of the reliability of market data in reflecting village offtake. We used data from urban markets and the villages that supply these markets to examine changes in the volume and composition of traded bushmeat between the village and the market (trade filters) in Equatorial Guinea. We collected data with market surveys and hunter offtake diaries. The trade filters varied depending on village remoteness and the monopoly power of traders. In a village with limited market access, species that maximized trader profits were most likely to be traded. In a village with greater market access, species for which hunters gained the greatest income per carcass were more likely to be traded. The probability of particular species being sold to market also depended on the capture method and season. Larger, more vulnerable species were more likely to be supplied from less‐accessible catchments, whereas there was no effect of forest cover or human population density on probability of being sold. This suggests that the composition of bushmeat offtake in an area may be driven more by urban demand than the geographic characteristics of that area. In one market, traders may have reached the limit of their geographical exploitation range, and hunting pressure within that range may be increasing. Our results demonstrate that it is possible to model the trade filters that bias market data, which opens the way to developing more robust market‐based sustainability indices for the bushmeat trade.     

KALMAN FILTER CALCULATION OF SAMPLING FREQUENCY WHEN DETERMINING ANNUAL MEAN SOLUTE CONCENTRATIONS

ABSTRACT: A linear filter (Kalman filter) technique was used with a Streamflow-concentration model the minimize surface water quality sampling frequencies when determining annual mean solute concentrations with a predetermined allowable error. The Kalman filter technique used the stream discharge interval as a replacement for the more commonly used time interval. Using filter computations, the measurement error variance was minimized within the sample size constraints. The Kalman filter application proposed here is applicable only under several conditions including: monitoring is solely to estimate annual mean concentration; discharge measurement errors are negligible; the Streamflow-concentration model is valid; and monthly samples reflect the total variance of the solute in question.     

BAYESIAN MODELS OF FORECASTED TIME SERIES1

Bayesian Processor of Forecasts (BPF) combines a prior distribution, which describes the natural uncertainty about the realization of a hydrologic process, with a likelihood function, which describes the uncertainty in categorical forecasts of that process, and outputs a posterior distribution of the process, conditional upon the forecasts. The posterior distribution provides a means of incorporating uncertain forecasts into optimal decision models. We present fundamentals of building BPF for time series. They include a general formulation, stochastic independence assumptions and their interpretation, computationally tractable models for forecasts of an independent process and a first-order Markov process, and parametric representations for normal-linear processes. An example is shown of an application to the annual time series of seasonal snowmelt runoff volume forecasts.     

VARIABILITY IN MEASURED BEDLO AD-TRANSPORT RATES1

ABSTRACT: Variability in bedload-transport rates during constant water discharge is an inherent part of the bedload-transport process. Although this variability has been measured extensively in the laboratory, similar information generally is not available from field measurements. During a four-day period of nearly constant water discharge, four sets of consecutively collected bedload samples, ranging from 43 to 120 samples, were obtained at the same cross channel location using a standard 65-pound Helley-Smith bedload sampler. When the measured transport rates are converted to dimensionless rates and plotted as cumulative frequency distributions, they show good agreement with a theoretical probability distribution function of rates derived for the case of ripples on dunes. The distributions show that during constant water discharge individual measured rates at a fixed point vary from near zero to four times the mean rate, and 60 percent of the sampled rates will be less than the mean. Because of the large variation in transport rates that occurs at every location in the cross section, many observations are required to establish an accurate estimate of the mean rate at any given location.     

IDENTIFICATION OF AQUIFER DISPERSIVITIES: METHODS OF ANALYSIS AND PARAMETER UNCERTAINTY1

ABSTRACT: This paper presents a method for estimating aquifer dispersivities in solute transport models. Sensitivity equations are derived for the calculation of sensitivity coefficients. A modified Gauss-Newton algorithm is used to perform the least-squares minimization. A statistical procedure is outlined to assess reliability of the estimated parameters. The solute transport model is solved by the upstream weighted, multiple cell balance method which combines the concepts of local mass balance and finite element approximations. A one-dimensional solute transport problem in a vertical column system is first used to illustrate the inverse technique. A second example considers the parameter identification problem for three-dimensional solute transport with a unidirectional steady and uniform flow field. The third example solves the parameter identification problem in a three-dimensional, stream-aquifer, solute transport system with steady state flow. Numerical experiments are conducted to study data requirements for parameter identification.     

STATISTICAL METHODS AND SAMPLING DESIGN FOR ESTIMATING STEP TRENDS IN SURFACE-WATER QUALITY1

ABSTRACT: This paper addresses two components of the problem of estimating the magnitude of step trends in surface water quality. The first is finding a robust estimator appropriate to the data characteristics expected in water-quality time series. The Hodges-Lehmann class of estimators is found to be robust in comparison to other nonparametric and moment-based estimators. A seasonal Hodges-Lehmann estimator is developed and shown to have desirable properties. Second, the effectiveness of various sampling strategies are examined using Monte Carlo simulation coupled with application of this estimator. The simulation is based on a large set of total phosphorus data from the Potomac River. To assure that the simulated records have realistic properties, the data are modeled in a multiplicative fashion incorporating flow, hysteresis, seasonal, and noise components. The results demonstrate the importance of balancing the length of the two sampling periods and balancing the number of data values between the two periods. The inefficiency of sampling at frequencies much in excess of 12 samples per year is demonstrated. Rotational sampling designs are discussed, and efficient designs, at least for this river and constituent, are shown to involve more than one year of active sampling at frequencies of about 12 per year.